Now showing items 1-20 of 245

    • How Much Do Unstated Problem Constraints Limit Deep Robotic Reinforcement Learning? 

      Lewis, W. Cannon II; Moll, Mark; Kavraki, Lydia E. (2019)
      Deep Reinforcement Learning is a promising paradigm for robotic control which has been shown to be capable of learning policies for high-dimensional, continuous control of unmodeled systems. However, Robotic Reinforcement Learning currently lacks clearly defined benchmark tasks, which makes it difficult for researchers to reproduce and compare against ...
    • Atlas + X: Sampling-based Planners on Constraint Manifolds 

      Voss, Caleb; Moll, Mark; Kavraki, Lydia E. (2017-06-14)
      Sampling-based planners struggle when the valid configurations are constrained to an implicit manifold. Special planners have been proposed for this problem recently. Our new framework is decoupled from any particular planner and augments existing algorithms not explicitly designed for constraint planning. We demonstrate the advantages of our generalized ...
    • Parallel Flow-Sensitive Points-to Analysis 

      Zhao, Jisheng; Burke, Michael G.; Sarkar, Vivek (2017-02-01)
      Points-to analysis is a fundamental requirement for many program analyses, optimizations, and debugging/verification tools. However, finding an effective balance between performance, scalability and precision in points-to analysis remains a major challenge. Many flow-sensitive algorithms achieve a desirable level of precision, but are impractical for ...
    • Algorithmic Improvements in Approximate Counting for Probabilistic Inference: From Linear to Logarithmic SAT Calls* 

      Chakraborty, Supratik; Meel, Kuldeep S.; Vardi, Moshe Y. (2016-11-28)
      Probabilistic inference via model counting has emerged as a scalable technique with strong formal guarantees, thanks to recent advances in hashing-based approximate counting. State-of-the-art hashing-based counting algorithms use an NP oracle (SAT solver in practice), such that the number of oracle invocations grows linearly in the number of variables ...
    • The Task Motion Kit 

      Chaudhuri, Swarat; Dantam, Neil T.; Kavraki, Lydia E. (2016-10-31)
      Expanding the capabilities of robots to achieve complex objectives in new environments requires novel reasoning systems. Everyday tasks in the physical world, such as the table setting in Fig. 1, couple discrete decisions about objects and actions with geometric decisions about collision free motion. Robotics has traditionally treated these issues—task ...
    • Leaky Buffer: A Novel Abstraction for Relieving Memory Pressure form Cluster Data Processing Frameworks 

      Liu, Zhaolei; Ng, T. S. Eugene (2016-03-25)
      The shift to the in-memory data processing paradigm has had a major influence on the development of cluster data processing frameworks. Numerous frameworks from the industry, open source community and academia are adopting the in-memory paradigm to achieve functionalities and performance breakthroughs. However, despite the advantages of these in ...
    • Elastic Tasks: Unifying Task Parallelism and SPMD Parallelism with an Adaptive Runtime 

      Agrawal, Kunal; Sarkar, Vivek; Sbîrlea, Alina (2015-02-11)
      In this paper, we introduce elastic tasks, a new high-level parallel programming primitive that can be used to unify task parallelism and SPMD parallelism in a common adaptive scheduling framework. Elastic tasks are internally parallel tasks and can run on a single worker or expand to take over multiple workers. An elastic task can be an ordinary ...
    • Synthesis of Integrated Task and Motion Plans from Plan Outlines Using SMT Solvers 

      Chaudhuri, Swarat; Kavraki, Lydia E.; Moll, Mark; Nedunuri, Srinivas; Prabhu, Sailesh; (2015-01-09)
      We present a new approach to integrated task and motion planning (ITMP) for robots performing mobile manipulation. In our approach, the user writes a high-level specification that captures partial knowledge about a mobile manipulation setting. In particular, this specification includes a plan outline that syntactically defines a space of plausible ...
    • COMMA: Coordinating the Migration of Multi-tier Applications 

      Liu, Zhaolei; Ng, T. S. Eugene; Sripanidkulchai, Kunwadee; Zheng, Jie (2014-11-24)
      Multi-tier applications are widely deployed in today’s virtualized cloud computing environments. At the same time, management operations in these virtualized environments, such as load balancing, hardware maintenance, workload consolidation, etc., often make use of live virtual machine (VM) migration to control the placement of VMs. Although existing ...
    • Automated Design, Implementation, and Evaluation of Arbiter-based PUF on FPGA using Programmable Delay Lines 

      Devadas, Srinivas; Kharaya, Akshat; Koushanfar, Farinaz; Majzoobi, Mehrdad (2014-08-18)
      This paper proposes a novel approach for automated implementation of an arbiter-based physical unclonable function (PUF) on field programmable gate arrays (FPGAs). We introduce a high resolution programmable delay logic (PDL) that is implemented by harnessing the FPGA lookup-table (LUT) internal structure. PDL allows automatic fine tuning of delays ...
    • λ group: Using Optics to Take Group Data Delivery in the Datacenter to the Next Degree 

      Bergman, Keren; Ng, T. S. Eugene; Sripanidkulchai, Kunwadee; Wang, Howard; Xia, Yiting (2014-02-17)
      The increasing number of datacenter applications with heavy one-to-many communications has raised the need for an efficient group data delivery solution. This paper presents an unconventional clean-slate architecture called λ group that uses optical networking technologies to enable ultra-fast, energy-efficient, low cost, and highly reliable group ...
    • BMS-CnC: Bounded Memory Scheduling of Dynamic Task Graphs 

      Budimlić, Zoran; Sarkar, Vivek; Sbîrlea, Dragoș (2013-10-24)
      It is now widely recognized that increased levels of parallelism is a necessary condition for improved application performance on multicore computers. However, as the number of cores increases, the memory-per-core ratio is expected to further decrease, making per-core memory efficiency of parallel programs an even more important concern in future ...
    • Pacer: Taking the Guesswork Out of Live Migrations in Hybrid Cloud Computing 

      Zheng, Jie; Ng, T. S. Eugene; Sripanidkulchai, Kunwadee; Liu, Zhaolei (2013-10-01)
      Hybrid cloud computing, where private and public cloud resources are combined and applications can migrate freely, ushers in unprecedented flexibility for businesses. To unleash the benefits, commercial products already enable the live migration of full virtual machines (CPU, memory, disk, network) between distant cloud datacenters. Unfortunately, ...
    • Plinko: Building Provably Resilient Forwarding Tables 

      Cox, Alan L.; Rixner, Scott; Stephens, Brent (2013-07-18)
      This paper introduces Plinko, a network architecture that uses a novel forwarding model and routing algorithm to build networks with forwarding paths that, assuming arbitrarily large forwarding tables, are provably resilient against t link failures, ∀t ∈ N. However, in practice, there are clearly limits on the size of forwarding tables. Nonetheless, ...
    • Interprocedural Strength Reduction of Critical Sections in Explicitly-Parallel Programs 

      Barik, Rajkishore; Sarkar, Vivek; Zhao, Jisheng (2013-05-01)
      In this paper, we introduce novel compiler optimization techniques to reduce the number of operations performed in critical sections that occur in explicitly-parallel programs. Specifically, we focus on three code transformations: 1) Partial Strength Reduction (PSR) of critical sections to replace critical sections by non-critical sections on certain ...
    • RCMP: A System Enabling Efficient Re-computation Based Failure Resilience for Big Data Analytics 

      Dinu, Florin; Ng, T. S. Eugene (2013-04-30)
      Multi-job I/O-intensive big-data computations can suffer a significant performance hit due to relying on data replication as the main failure resilience strategy. Data replication is inherently an expensive operation for I/O-intensive jobs because the datasets to be replicated are very large. Moreover, since the failure resilience guarantees provided ...
    • User-Specified and Automatic Data Layout Selection for Portable Performance 

      Karlin, Ian; Keasler, Jeff; McGraw, James R.; Sarkar, Vivek; Sharma, Kamal (2013-04-25)
      This paper describes a new approach to managing array data layouts to optimize performance for scientific codes. Prior research has shown that changing data layouts (e.g., interleaving arrays) can improve performance. However, there have been two major reasons why such optimizations are not widely used: (1) the need to select different layouts for ...
    • Automatic Detection of Inter-application Permission Leaks in Android Applications 

      Burke, Michael G.; Guarnieri, Salvatore; Pistoia, Marco; Sarkar, Vivek; Sbîrlea, Dragoș (2013-01-23)
      Due to their growing prevalence, smartphones can access an increasing amount of sensitive user information. To better protect this information, modern mobile operating systems provide permission-based security, which restricts applications to only access a clearly defined subset of system APIs and user data. The Android operating system builds upon ...
    • AutoDock-based incremental docking protocol improves docking of large ligands 

      Dhanik, Ankur; Kavraki, Lydia E.; McMurray, John S. (2012-10-07)
      It is well known that computer-aided docking of large ligands, with many rotatable bonds, is extremely difficult. AutoDock is a widely used docking program that can dock small ligands, with up to 5 or 6 rotatable bonds, accurately and quickly. Docking of larger ligands, however, is not very accurate and is computationally expensive. In this paper we ...
    • Scalable and Precise Dynamic Datarace Detection for Structured Parallelism 

      Raman, Raghavan; Zhao, Jisheng; Sarkar, Vivek; Vechev, Martin; Yahav , Eran (2012-07-06)
      Existing dynamic race detectors suffer from at least one of the following three limitations: i) space overhead per memory location grows linearly with the number of parallel threads [13], severely limiting the parallelism that the algorithm can handle. (ii) sequentialization: the parallel program must be processed in a sequential order, usually ...